Hi All,
I performed a shape analysis using FSL_First to correlate performance in a navigation task with shape differences in the caudate. I followed the instructions listed in the wiki for the design matrix:
"Design matrix with one column (EV) where each row contains the value of the correlating measure for each subject in the same order as the subject's bvars (in the concatenated bvars file)".
This worked well, but now I struggle with the interpreation of those results. For example after correction for multiple comparison I reveal a difference in shape in the anterior caudate nucleus.
But how would I interprete that?
The wiki gives the following explanation:
"Interpretting the results of a correlation: the values in the p-value images will give the probability of a zero correlation (the null hypothesis) at each vertex."
My null hypothesis would be that performance would not correlate with shape of the caudate
Let's assume I would get a p-value of 0.05, would that mean that in the anterior caudate I can reject the null hypothesis?
I would be happy for any suggestions to that topic. I read several papers that used a correlation with VBM but unfortunately non that did the same for shape analysis.
Many Thanks
Stefanie
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